ParallelReader Component: Performance Boost in Data Processing

In October release 2.8.1 of Clover we introduced a new component which definitely should attract your attention – the Parallel Reader. The name itself already suggests the goal of the component – improve reading speed by going parallel. The component is very similar to Universal Data Reader in function – it reads delimited flat files like CSV, tab delimited, etc. – much hasn’t changed here. But the real difference comes from under the hood.

There are two major optimizations which allow Parallel Reader to exhibit excellent performance results, especially on server-class machines with fast modern disks or better yet, disk arrays. The first optimization we have done is – of course – reading the file in parallel. The input file is divided into a set of virtual data chunks which are fed into reading threads. These work all together at the same time – each one parsing data records just from its own file part. The number of threads can be specified by component parameter “Level Of Parallelism” and should reflect the hardware setup – e.g. number of disks in a stripped RAID – to harness the maximum power of Parallel Reader. Another great performance gain we achieved is merely by just simplifying the data parser inside. This parser is as simple as possible – although with limited validation, error handling, and some functionality – but really, really fast.

Although the new reader has a few limitations coming from its nature, extreme speed in common use cases compensates all these drawbacks. If you are processing big amounts of data (hundreds of megabytes and more) and your transformation does not depend on data records being read in original order, Parallel Reader is here and it might just be the right choice for you – why not give it a try?